Shooting Methods for Parameter Estimation of Output Error Models. Ribeiro, A. H. & Aguirre, L. A. IFAC-PapersOnLine, 50(1):13998–14003, July, 2017.
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This paper studies parameter estimation of output error (OE) models. The commonly used approach of minimizing the free-run simulation error is called single shooting in contrast with the new multiple shooting approach proposed in this paper, for which the free-run simulation error of sub-datasets is minimized subject to equality constraints. The names “single shooting” and “multiple shooting” are used due to the similarities with techniques for estimating ODE (ordinary differential equation) parameters. Examples with nonlinear polynomial models illustrate the advantages of OE models as well as the capability of the multiple shooting approach to avoid undesirable local minima.
@article{ribeiro_shooting_2017,
	title = {Shooting {Methods} for {Parameter} {Estimation} of {Output} {Error} {Models}},
	volume = {50},
	issn = {2405-8963},
	doi = {10/gfjwmp},
	abstract = {This paper studies parameter estimation of output error (OE) models. The commonly used approach of minimizing the free-run simulation error is called single shooting in contrast with the new multiple shooting approach proposed in this paper, for which the free-run simulation error of sub-datasets is minimized subject to equality constraints. The names “single shooting” and “multiple shooting” are used due to the similarities with techniques for estimating ODE (ordinary differential equation) parameters. Examples with nonlinear polynomial models illustrate the advantages of OE models as well as the capability of the multiple shooting approach to avoid undesirable local minima.},
	number = {1},
	journal = {IFAC-PapersOnLine},
	author = {Ribeiro, Antônio H. and Aguirre, Luis A.},
	month = jul,
	year = {2017},
	keywords = {Multiple shooting, nonlinear least-squares, output error models, simulation error minimization},
	pages = {13998--14003},
}

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